code: def naive_upsample_2d(x, factor=2):
      _N, C, H, W = x.shape
      x = torch.reshape(x, (-1, C, H, 1, W, 1))
      x = x.repeat(1, 1, 1, factor, 1, factor)
      return torch.reshape(x, (-1, C, H * factor, W * factor))
  
file_path: espnet/espnet2/enh/layers/ncsnpp_utils/up_or_down_sampling.py
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from espnet2.enh.layers.ncsnpp_utils.upfirdn2d import upfirdn2d
label_desc: Use image node_id 2 for calling a global function with example usage: naive_upsample_2d(x, factor) and returns: torch